ArticleInternational journal of general medicine2021
Integrated Bioinformatics Analysis to Identify Abnormal Methylated Differentially Expressed Genes for Predicting Prognosis of Human Colon Cancer.
Article in International journal of general medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Plasma cell signatures predict prognosis and treatment efficacy for lung adenocarcinoma.Cellular oncology (Dordrecht, Netherlands) · 2024Article
- The construction and validation of ECM-related prognosis model in laryngeal squamous cell carcinoma.Heliyon · 2023Article
- Identification of differentially expressed genes induced by aberrant methylation in acute myeloid leukemia using integrated bioinformatics analyses.Oncology letters · 2022Article
- ordinalbayes: Fitting Ordinal Bayesian Regression Models to High-Dimensional Data Using R.Stats · 2022Article
- Functional impact of multi-omic interactions in breast cancer subtypes.Frontiers in genetics · 2022Article
- Association of environmental exposure to chromium with differential DNA methylation: An epigenome-wide study.Frontiers in genetics · 2022Article
- A Novel Cancer Stemness-Related Signature for Predicting Prognosis in Patients with Colon Adenocarcinoma.Stem cells international · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo identify the value of key differentially expressed genes (DEGs) regulated by differentially methylated regions (DMRs) in predicting the prognosis of human colon cancer. MATERIALS AND
methodsRNA sequencing data and DNA methylation data of 455 colon adenocarcinoma (COAD) cases and 41 normal controls were downloaded from The Cancer Genome Atlas (TCGA). Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by the DAVID database. To identify the hub genes regulated by methylation, univariate Cox and multivariate Cox regression analyses were carried out. A nomogram based on the risk score was built to identify the power of the hub genes to predict prognosis in patients with colon cancer.
resultsA total of 133 DEGs regulated by DMRs were identified through analyzing RNA sequencing data and DNA methylation data from TCGA. GO functional enrichment and KEGG pathway enrichment analysis showed the genes involved in the initiation and progression of colon cancer. Univariate Cox regression analysis and multivariate Cox regression analysis focused on the seven hub genes (
conclusionOur findings suggest that the DEGs regulated by DMRs are involved in the carcinogenesis and development of colon cancer, and the aberrantly methylated DEGs associated with overall survival of patients may be potential diagnostic and therapeutic targets for colon cancer.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.